In a radio resource manager (RRM) of a power-controlled wireless communication system, there are advantages to being able to accurately predict the increase in interference resulting from the addition of a connection to the system. The term “connection” denotes an association between a wireless transmit/receive unit (WTRU) and a base station, whereby the WTRU transmits information to be received by the base station (uplink connection), or the base station transmits information to be received by the WTRU (downlink connection). A WTRU may be connected or disconnected from a communication link with the base station, or for that matter, with the network. The addition or deletion of a connection between a WTRU and a base station is a “connection event”. The WTRU can have one or several connections at a single time.
The capability of predicting the increase of interference permits the system to make more accurate decisions regarding whether or not the connection should be allowed, and what resources should be allocated to it. This is typically referred to as call admission control or, when choosing the time slots where the physical channels of a user should be allocated, is referred to as fast dynamic resource allocation. Also of interest to some algorithms is the prediction of the decrease of interference following the departure of a connection, or the de-allocation of the physical channels of a user from a time slot.
In a wireless system employing power control, the transmission power of each connection is dynamically adjusted in such a way that the quality of service criterion, such as the block error rate (BLER) or the signal-to-interference ratio (SIR), is just met. The use of power control generally increases the capacity of the system because it minimizes the transmission power of each connection and thus, the interference it causes to other users.
To illustrate the relevance of estimating beforehand the increase of interference following the addition of a connection to the system, consider the following scenario. A given WTRU, such as WTRU A, requests a new downlink connection to the system. After the system grants this new connection, the base station serving WTRU A commences transmission, requiring a certain amount of additional power. This additional transmitted power results in additional interference to other WTRUs, such as WTRU B and WTRU C, already connected to the system and served by the same or other base stations. As a result of this additional interference, the base station(s) serving WTRUs B and C must increase their transmission powers so that the downlink connections to WTRUs B and C maintain their SIR to the required value. This in turn results in additional interference to WTRU A, with a consequent increase of transmission power by the base station serving WTRU A.
The cycle continues until one of the following two possibilities happen: 1) the transmission power and interference levels converge and stabilize to values such that the minimum SIR of all served WTRUs can be achieved; or 2) the transmission power and interference levels constantly increase until the maximum transmission power of the base stations is reached, and the minimum SIR of the served WTRUs is no longer achieved. This latter possibility is of course undesirable and could be avoided if the system had the ability to estimate the resulting increase of interference before the acceptance of a new connection. Although the scenario described applies to the downlink (i.e. a base station-to-WTRU connection), a similar scenario exists for the uplink (i.e. WTRU-to-base station connection).
One estimation technique for a Frequency Division Duplex (FDD) system using Code Division Multiple Access (CDMA) estimates the increase in uplink interference. This technique applies to an FDD/CDMA system where a user connected to a given cell sustains significant interference from other users connected to that cell, (i.e. intra-cell interference). The technique is based on first estimating the “load factor” of a candidate user based on the anticipated required SIR of the user, and to use this load factor along with the load factor of the candidate serving cell to estimate the interference increase.
The technique of estimating the load factor does not apply well to systems where intra-cell interference is negligible compared to interference coming from other cells, (i.e. inter-cell interference). One example would be a system based on one of the TDD modes (1.28 Mcps or 3.84 Mcps) of the UTRA standard. In such a system, base stations as well as WTRUs are equipped with a multi-user detector which has the ability to significantly reduce the interference coming from users connected to the same cell.
Elimination of intra-cell interference is theoretically possible in FDD/CDMA systems as well, but is generally not implemented in current systems due to its complexity. In systems where intra-cell interference is negligible, a possible technique is to base the interference rise or fall estimation on several input parameters, including measurements reported by the user and/or the cell to which it is connected. Such an approach is classified as “measurement-based”.
The currently favored specific approach to interference rise estimation is the use of look-up tables. It consists of using the following input elements: 1) expected required SIR of the connection for the user to sustain adequate quality of service; 2) path loss to the serving or potentially serving base station; and 3) level of inter-cell interference including thermal noise, (in the concerned time slots if time-slotted). The concerned time slots are, in the case of a connection addition, the candidate time slots where the connection can potentially be supported. In case of a connection deletion, the concerned time slots are the time slots currently supporting the connection.
This information is used in conjunction with look-up tables. There are two sets of tables, one set for connection addition (“noise rise tables”) and one set for connection deletion (“noise fall tables”). The noise rise/fall look-up tables are pre-stored in the radio network controller (RNC). The look-up tables are pre-calculated for the specific deployment scenario in which the system is operating. A deployment scenario is defined in terms of cell radius, propagation environment, base station antenna properties, etc. The look-up tables take the three above-mentioned input elements and return a single value of the estimated increase or decrease of interference in dB. However, the generation of look-up tables for a specific deployment scenario is a non-trivial task involving simulations or measurement collecting, as well as sophisticated statistical analysis.
The prior art schemes for estimating interference rise have certain disadvantages. This is significant with regard to CDMA/FDD systems, in which the load factor of a candidate user is estimated based on the anticipated required SIR. The user intra-cell interference in such estimations is not negligible. The method and formulas used to estimate the load factor in a CDMA/FDD system cannot be effectively applied to a TDD system.
As applied to CDMA/TDD systems, where intra-cell interference is negligible due to the presence of multi-user detection, the use of look-up tables is simple in concept but difficult to implement. First, it is particularly difficult to obtain tables that are suitable for every possible deployment scenario. If tables are obtained from statistical analysis of system level simulation results, a separate analysis must be performed for each possible deployment (e.g., indoor, micro-cellular, urban macro). In each case the results are dependent on several factors such as the path loss propagation model, the noise figure of the various devices and the number of cells in the system. It is unlikely that a given table will provide accurate predictions with an acceptable performance in all deployment situations. Additionally, even if the system is deployed in the same general type of environment as what was simulated, differences between the simulated deployment and the actual deployment are likely to be sufficient to bias the predictions.
Second, from a practical aspect, the process of building a table with a tri-dimensional input and thereafter implementing the table in a simulation tool is a complex, error-prone task.
Accordingly, it would be desirable to have a system and method which efficiently and accurately estimates the effect of an addition or deletion of a connection in a power-controlled wireless system.